Modeling the Transport and Deposition of ¹⁰Be Produced by the Strongest Solar Proton Event During the Holocene

Prominent excursions in the number of cosmogenic nuclides (e.g., ¹⁰Be) around 774 CE/775 document the most severe solar proton event (SPE) throughout the Holocene. Its manifestation in ice cores is valuable for geochronology, but also for solar-terrestrial physics and climate modeling. Using the ECHAM/MESSy Atmospheric Chemistry (EMAC) climate model in combination with the Warning System for Aviation Exposure to SEP (WASAVIES), we investigate the transport, mixing, and deposition of the cosmogenic nuclide ¹⁰Be produced by the 774 CE/775 SPE. By comparing the model results to the reconstructed ¹⁰Be time series from four ice core records, we study the atmospheric pathways of ¹⁰Be from its stratospheric source to its sink at Earth's surface. The reconstructed post-SPE evolution of the ¹⁰Be surface fluxes at the ice core sites is well captured by the model. The downward transport of the ¹⁰Be atoms is controlled by the Brewer-Dobson circulation in the stratosphere and cross-tropopause transport via tropopause folds or large-scale sinking. Clear hemispheric differences in the transport and deposition processes are identified. In both polar regions the ¹⁰Be surface fluxes peak in summertime, with a larger influence of wet deposition on the seasonal ¹⁰Be surface flux in Greenland than in Antarctica. Differences in the peak ¹⁰Be surface flux following the 774 CE/775 SPE at the drilling sites are explained by specific meteorological conditions depending on the geographic locations of the sites

Dynamic Changes of Circulating Tumor DNA Predict Clinical Outcome in Patients With Advanced Non-Small-Cell Lung Cancer Treated With Immune Checkpoint Inhibitors

PURPOSE Immune checkpoint inhibitors (ICIs) are increasingly being used in non-small-cell lung cancer (NSCLC), yet biomarkers predicting their benefit are lacking. We evaluated if on-treatment changes of circulating tumor DNA (ctDNA) from ICI start (t0) to after two cycles (t1) assessed with a commercial panel could identify patients with NSCLC who would benefit from ICI. PATIENTS AND METHODS The molecular ctDNA response was evaluated as a predictor of radiographic tumor response and long-term survival benefit of ICI. To maximize the yield of ctDNA detection, de novo mutation calling was performed. Furthermore, the impact of clonal hematopoiesis (CH)-related variants as a source of biologic noise was investigated. RESULTS After correction for CH-related variants, which were detected in 75 patients (44.9%), ctDNA was detected in 152 of 167 (91.0%) patients. We observed only a fair agreement of the molecular and radiographic response, which was even more impaired by the inclusion of CH-related variants. After exclusion of those, a ≥ 50% molecular response improved progression-free survival (10 v 2 months; hazard ratio [HR], 0.55; 95% CI, 0.39 to 0.77; P =.0011) and overall survival (18.4 v 5.9 months; HR, 0.44; 95% CI, 0.31 to 0.62; P,.0001) compared with patients not achieving this end point. After adjusting for clinical variables, ctDNA response and STK11/KEAP1 mutations (HR, 2.08; 95% CI, 1.4 to 3.0; P,.001) remained independent predictors for overall survival, irrespective of programmed death ligand-1 expression. A landmark survival analysis at 2 months (n = 129) provided similar results. CONCLUSION On-treatment changes of ctDNA in plasma reveal predictive information for long-term clinical benefit in ICI-treated patients with NSCLC. A broader NSCLC patient coverage through de novo mutation calling and the use of a variant call set excluding CH-related variants improved the classification of molecular responders, but had no significant impact on survival

Deep learning-assisted radiomics facilitates multimodal prognostication for personalized treatment strategies in low-grade glioma

Determining the optimal course of treatment for low grade glioma (LGG) patients is challenging and frequently reliant on subjective judgment and limited scientific evidence. Our objective was to develop a comprehensive deep learning assisted radiomics model for assessing not only overall survival in LGG, but also the likelihood of future malignancy and glioma growth velocity. Thus, we retrospectively included 349 LGG patients to develop a prediction model using clinical, anatomical, and preoperative MRI data. Before performing radiomics analysis, a U2-model for glioma segmentation was utilized to prevent bias, yielding a mean whole tumor Dice score of 0.837. Overall survival and time to malignancy were estimated using Cox proportional hazard models. In a postoperative model, we derived a C-index of 0.82 (CI 0.79-0.86) for the training cohort over 10 years and 0.74 (Cl 0.64-0.84) for the test cohort. Preoperative models showed a C-index of 0.77 (Cl 0.73-0.82) for training and 0.67 (Cl 0.57-0.80) test sets. Our findings suggest that we can reliably predict the survival of a heterogeneous population of glioma patients in both preoperative and postoperative scenarios. Further, we demonstrate the utility of radiomics in predicting biological tumor activity, such as the time to malignancy and the LGG growth rate

Modeling Evolutionary Dynamics of Epigenetic Mutations in Hierarchically Organized Tumors

The cancer stem cell (CSC) concept is a highly debated topic in cancer research. While experimental evidence in favor of the cancer stem cell theory is apparently abundant, the results are often criticized as being difficult to interpret. An important reason for this is that most experimental data that support this model rely on transplantation studies. In this study we use a novel cellular Potts model to elucidate the dynamics of established malignancies that are driven by a small subset of CSCs. Our results demonstrate that epigenetic mutations that occur during mitosis display highly altered dynamics in CSC-driven malignancies compared to a classical, non-hierarchical model of growth. In particular, the heterogeneity observed in CSC-driven tumors is considerably higher. We speculate that this feature could be used in combination with epigenetic (methylation) sequencing studies of human malignancies to prove or refute the CSC hypothesis in established tumors without the need for transplantation. Moreover our tumor growth simulations indicate that CSC-driven tumors display evolutionary features that can be considered beneficial during tumor progression. Besides an increased heterogeneity they also exhibit properties that allow the escape of clones from local fitness peaks. This leads to more aggressive phenotypes in the long run and makes the neoplasm more adaptable to stringent selective forces such as cancer treatment. Indeed when therapy is applied the clone landscape of the regrown tumor is more aggressive with respect to the primary tumor, whereas the classical model demonstrated similar patterns before and after therapy. Understanding these often counter-intuitive fundamental properties of (non-)hierarchically organized malignancies is a crucial step in validating the CSC concept as well as providing insight into the therapeutical consequences of this model

A critical evaluation of decadal solar cycle imprints in the MiKlip historical ensemble simulations

Studies concerning solar–terrestrial connections over the last decades claim to have found evidence that the quasi-decadal solar cycle can have an influence on the dynamics in the middle atmosphere in the Northern Hemisphere (NH) during the winter season. It has been argued that feedbacks between the intensity of the UV part of the solar spectrum and low-latitude stratospheric ozone may produce anomalies in meridional temperature gradients which have the potential to alter the zonal-mean flow in middle to high latitudes. Interactions between the zonal wind and planetary waves can lead to a downward propagation of the anomalies, produced in the middle atmosphere, down to the troposphere. More recently, it has been proposed that top-down-initiated decadal solar signals might modulate surface climate and synchronize the North Atlantic Oscillation. A realistic representation of the solar cycle in climate models was suggested to significantly enhance decadal prediction skill. These conclusions have been debated controversial since then due to the lack of realistic decadal prediction model setups and more extensive analysis. In this paper we aim for an objective and improved evaluation of possible solar imprints from the middle atmosphere to the surface and with that from head to toe. Thus, we analyze model output from historical ensemble simulations conducted with the state-of-the-art Max Planck Institute for Meteorology Earth System Model in high-resolution configuration (MPI-ESM-HR). The target of these simulations was to isolate the most crucial model physics to foster basic research on decadal climate prediction and to develop an operational ensemble decadal prediction system within the “Mittelfristige Klimaprognose” (MiKlip) framework. Based on correlations and multiple linear regression analysis we show that the MPI-ESM-HR simulates a realistic, statistically significant and robust shortwave heating rate and temperature response at the tropical stratopause, in good agreement with existing studies. However, the dynamical response to this initial radiative signal in the NH during the boreal winter season is weak. We find a slight strengthening of the polar vortex in midwinter during solar maximum conditions in the ensemble mean, which is consistent with the so-called “top-down” mechanism. The individual ensemble members, however, show a large spread in the dynamical response with opposite signs in response to the solar cycle, which might be a result of the large overall internal variability compensating for rather small solar imprints. We also analyze the possible surface responses to the 11-year solar cycle and review the proposed synchronization between the solar forcing and the North Atlantic Oscillation. We find that the simulated westerly wind anomalies in the lower troposphere, as well as the anomalies in the mean sea level pressure, are most likely independent from the timing of the solar signal in the middle atmosphere and the alleged top-down influences. The pattern rather reflects the decadal internal variability in the troposphere, mimicking positive and negative phases of the Arctic and North Atlantic oscillations throughout the year sporadically, which is then assigned to the solar predictor time series without any plausible physical connection and sound solar contribution. Finally, by applying lead–lag correlations, we find that the proposed synchronization between the solar cycle and the decadal component of the North Atlantic Oscillation might rather be a statistical artifact, affected for example by the internal decadal variability in the ocean, than a plausible physical connection between the UV solar forcing and quasi-decadal variations in the troposphere.</p